AIMC Topic: Neural Networks, Computer

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Equivariant Line Graph Neural Network for Protein-Ligand Binding Affinity Prediction.

IEEE journal of biomedical and health informatics
Binding affinity prediction of three-dimensional (3D) protein-ligand complexes is critical for drug repositioning and virtual drug screening. Existing approaches usually transform a 3D protein-ligand complex to a two-dimensional (2D) graph, and then ...

MSDE-Net: A Multi-Scale Dual-Encoding Network for Surgical Instrument Segmentation.

IEEE journal of biomedical and health informatics
Minimally invasive surgery, which relies on surgical robots and microscopes, demands precise image segmentation to ensure safe and efficient procedures. Nevertheless, achieving accurate segmentation of surgical instruments remains challenging due to ...

SMARTSeiz: Deep Learning With Attention Mechanism for Accurate Seizure Recognition in IoT Healthcare Devices.

IEEE journal of biomedical and health informatics
The Internet of Things (IoT) is capable of controlling the healthcare monitoring system for remote-based patients. Epilepsy, a chronic brain syndrome characterized by recurrent, unpredictable attacks, affects individuals of all ages. IoT-based seizur...

LDMRes-Net: A Lightweight Neural Network for Efficient Medical Image Segmentation on IoT and Edge Devices.

IEEE journal of biomedical and health informatics
In this study, we propose LDMRes-Net, a lightweight dual-multiscale residual block-based convolutional neural network tailored for medical image segmentation on IoT and edge platforms. Conventional U-Net-based models face challenges in meeting the sp...

Predicting recovery following stroke: Deep learning, multimodal data and feature selection using explainable AI.

NeuroImage. Clinical
Machine learning offers great potential for automated prediction of post-stroke symptoms and their response to rehabilitation. Major challenges for this endeavour include the very high dimensionality of neuroimaging data, the relatively small size of...

A deep neural network prediction method for diabetes based on Kendall's correlation coefficient and attention mechanism.

PloS one
Diabetes is a chronic disease, which is characterized by abnormally high blood sugar levels. It may affect various organs and tissues, and even lead to life-threatening complications. Accurate prediction of diabetes can significantly reduce its incid...

Directly training temporal Spiking Neural Network with sparse surrogate gradient.

Neural networks : the official journal of the International Neural Network Society
Brain-inspired Spiking Neural Networks (SNNs) have attracted much attention due to their event-based computing and energy-efficient features. However, the spiking all-or-none nature has prevented direct training of SNNs for various applications. The ...

Mittag-Leffler stability and application of delayed fractional-order competitive neural networks.

Neural networks : the official journal of the International Neural Network Society
In the article, the Mittag-Leffler stability and application of delayed fractional-order competitive neural networks (FOCNNs) are developed. By virtue of the operator pair, the conditions of the coexistence of equilibrium points (EPs) are discussed a...

Progressive Neighbor-masked Contrastive Learning for Fusion-style Deep Multi-view Clustering.

Neural networks : the official journal of the International Neural Network Society
Fusion-style Deep Multi-view Clustering (FDMC) can efficiently integrate comprehensive feature information from latent embeddings of multiple views and has drawn much attention recently. However, existing FDMC methods suffer from the interference of ...

Continual pre-training mitigates forgetting in language and vision.

Neural networks : the official journal of the International Neural Network Society
Pre-trained models are commonly used in Continual Learning to initialize the model before training on the stream of non-stationary data. However, pre-training is rarely applied during Continual Learning. We investigate the characteristics of the Cont...